AI AGENT UTILIZATION METHODOLOGY TO BUILD A LOGISTICS INFORMATION INTEGRATION PLATFORM

초록

Amid the Fourth Industrial Revolution and the increasing complexity of global supply chains, the logistics industry demands platforms capable of real-time data integration and analysis. Traditional logistics platforms have primarily focused on data collection and storage, with limited support for intelligent interpretation and policy development. This study proposes a methodology for applying AI Agent-based systems to addressing these limitations. By integrating a unified data layer with an AI Agent layer, the proposed approach autonomously performs advanced tasks such as inventory forecasting, route optimization, anomaly detection, and policy simulation. A cooperative agent architecture improves analytical accuracy and responsiveness, while offering an intuitive interface for non-experts. The proposed integrated data platform is expected to enhance operational efficiency and support policy formulation. Future research will focus on prototype development and empirical validation. © 2026, ICIC International. All rights reserved.

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